1. Course : Artificial Intelligence
Introduction to Artificial Intelligence Prof. Dr. Ir. Widodo Budiharto 2019

2. T0264 - Artificial Intelligence
Father of AI
"The Dartmouth summer research project on artificial intelligence”
Jhon McCarthy, The father of AI
T Artificial Intelligence

3. Artificial Intelligence
Artificial intelligence (AI)
the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages

4. What is AI? Thinking Humanly
“The exciting new effort to make computers thinks … machine with minds, in the full and literal sense”
(Haugeland, 1985)
Thinking Rationally
“The study of mental faculties through the use of computational models”
(Charniak and McDermott, 1985)
Acting Humanly
“The study of how to make computers do things at which, at the moment, people are better” (Rich and Knight, 1991)
Acting Rationally
“Computational Intelligence is the study of the design of intelligent agents”
(Poole et al., 1998)

5. Acting humanly The Turing Test (Alan Turing, 1950)
Instead of duplicating an exemplar, it is more useful and important to study the principles of the intelligence

6. Thinking humanly The cognitive modelling Part of cognitive science
Once we have a sufficiently precise theory of the mind, it becomes possible to express the theory as a computer program

7. Thinking rationally The “laws of thought” or logic
Aristotle was one of the first to introduce logic or “right thinking”
Syllogisms provided patterns for argument structure
Correct premises = correct solutions
Example:
He is a boy; All boys are handsome;
Therefore, he is handsome

8. Acting rationally Rational behavior: doing the right thing
The right thing: that which is expected to maximize goal achievement given the available information
Example:
Given money Rp , you have to buy a birthday gift
Which one will you choose? Which one is more rational?
Bracelet (Rp ) or Ring (Rp )

9. Rational Agent An agent Just something that acts A rational agent
One that acts as to achieve the best (expected) outcome
The rational-agent approach has two advantages:
It is more general than the “laws of thought” approach
it is more amenable to scientific development

10. Demo
Robot Edukasi EduRobot

11. AI Applications Speech Recognition Virtual Assistants Siri (Apple)
Google Now
Cortana (Microsoft)
They helps us to arrange meetings, check weather, do a phone call, send a message, etc.
[source]

12. AI Applications Machine Translation Google Translate
No more bringing dictionary when travelling
[source]

13. AI Applications Robotics
Several robots were sent to Fukushima nuclear tragedy to perform various tasks (Left)
Hubo: A KAIST Robot who wins the DARPA Robot Challenge (Right)
[source]
[source]

14. AI Applications Recommendation Systems
AI helps to provide items / photos / various things based on our social activities
Instagram Explore / Search Feed
If we follow many badminton accounts, they show:

15. AI Applications Search Engines
Google’s search engines algorithm is designed to show internet pages of our interests in a blink of eyes

16. AI Applications Email Spam/Junk email detection Sender:
Title:
Hi, I need your help!
1 million dollar for you now!
[blank]
Content:
Congrats, you won XXX Awards. Please tell me your name, address, birth date, and telephone number to

17. AI Applications
Face Detection
[source]

18. AI Applications Face Recognition
China’s facial recognition technology to identify the citizen
[source]

19. AI Applications Games Chess (1997): Kasparov vs. IBM Deep Blue
Powerful search algorithms
Jeopardy! (2011): Humans vs. IBM Watson
Natural language processing and information extraction
Go (2016): Lee Sedol vs. Google AlphaGo
Deep learning + reinforcement learning + search algorithms!
Future: 5 vs 5 AI for Dota

20. AI Applications Games March 2016, AlphaGo beat Lee Sedol (4 vs 1)
December 2016, AlphaGo beat Ke Jie (3 vs 0)
[source]
[source]

21. AI Applications Autonomous Driving
NuTonomy: A robo-taxi service in Singapore
[source]

22. AI Applications Autonomous Driving
Waymo: An autonomous car company under Alphabet, Inc. (Google’s parent company)
[source]

23. Control Theory and Cybernetics
Foundation of AI AI
Philosophy
Mathematics
Economics
Neuroscience
Psychology
Computer Engineering
Control Theory and Cybernetics
Linguistics

24. Foundation of AI Philosophy Logic, methods of reasoning
Foundations of learning, language, rationality
Mathematics
Logic: Formal representation and proof
Algorithms, computation, (un)decidability, (in)tractability
Probability

25. Foundation of AI Economics Formal theory of rational decisions
Neuroscience
Plastic physical substrate for mental activity
Psychology
Adaptation
Phenomena of perception and motor control
Experimental techniques (psychophysics, etc.)

26. Foundation of AI Computer Engineering
How can we build an efficient computer to build AI program?
Control Theory and Cybernetics
Simple optimal agent designs
Linguistics
Knowledge representation
Grammar

27. Brief History of AI

28. Agent
An agent is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through actuators.

29. Agent A vacuum-cleaner world with just two locations
Percept: location and contents, i.e. [A, Dirty]
Actions: Left, Right, Suck, NoOp

30. Agent
Partial tabulation of the simple agent function

31. Concept of Rationality
Definition of a rational agent:
For each possible percept sequence, a rational agent should select an action that is expected to maximize its performance measure, given the evidence provided by the percept sequence and whatever built-in knowledge the agent has.

32. Task Environments
To build a rational agent, we need to first define the PEAS:
P (Performance)
E (Environment)
A (Actuators)
S (Sensors)

33. What is PEAS for? Autonomous car
[source]
Autonomous car
Performance: safety, destination, legality, comfort
Environment: streets, pedestrian, highway, weather
Actuators: steering, accelerator, brake, horn
Sensors: video, GPS, accelerometer, keyboard

34. Structure of Intelligent Agents
Agent = Architecture + Program
Architecture is the hardware
Sensors + Actuators
Program is the software
Program

35. Agent Types Four basic type of agents: Simple reflex agents
Modal-based reflex agents
Goal-based agents
Utility-based agents
All of which can be generalized into learning agents that can improve their performance and generate better actions.

36. Simple Reflex Agents
An action is done based on the current state only. Ignore the sensors history.

37. Modal-based Reflex Agents
The sensors and actions history is used to model the world / environment. An action is done based on the world model.

38. Goals-based Agents
An action is done based on the combined information from the world model and goal information.

39. Utility-based Agents
An action is done based on the agent happiness (utility).
It is the agent’s performance measure.

40. Learning Agents
Programming agents by hand can be very tedious. Some more expeditious method seem desirable" Alan Turing, 1950.

41. Expert Systems

42. (1 group : 4-5 persons, 50 minutes)
Presentation Topics
(1 group : 4-5 persons, 50 minutes)
Searching methods (principles, algorithm and demo in C#/Python)
First Order Logic and Inference in First Order Logic
Computer Vision ( principles and Demo in OpenCV)
Robotics and Robot Vision (Simple Demo using Arduino Codes/OpenCV)
Machine Learning k-NN and SVM (Simple Demo using C#/Python)
Reasoning with Uncertainty (principles and algorithm and demo in C#/Python)
Knowledge representation and Planning and Acting in the Real World
Fuzzy Logic (principles and demo in C#/Python)
Neural Networks and Deep learning (principles and demo in C#)
Bayesian & Probabilistic Reasoning Over Time ( principles and demo in C#)
Making simple and complex decisions (principles and demo in C#)
Natural Language Processing
Starting at the second week, create the power point presentation,summary in Ms Word and demo code send to
T Artificial Intelligence

43. Project Presentation on Session 25-26 Kelompok 4-5 orang/grup
Buat Aplikasi AI yang berguna menggunakan Python, Arduino, OpenCV atau mobile apps.
Dapat digunakan untuk lomba PKM-KC dan dikembangkan untuk Skripsi.
Dipresentasikan menggunakan ppt secara kelompok di pertemuan 12-13
Softcopy Laporan berbentuk paper 5-8 halaman dengan nama yang lengkap dapat dikirim ke

44. Homework Explain the definition of AI
Create a program using Python for displaying image
import numpy as np
import cv2
# Load an color image in grayscale
img = cv2.imread('messi5.jpg',0)
cv2.imshow('image',img)
cv2.waitKey(0)
cv2.destroyAllWindows()

45. Kelompok Presentasi(7 orang/kelompok) sertakan demo Program
Search Strategies, Local Search and Adversarial Search
Logical Agents and First Order Logic
Fuzzy Systems and Implementation
Computer Vision, Robot and Robot Vision
Natural Language Processing
Quantifying Uncertainty
Machine Learning and Big Data
Probabilistic Reasoning and Probabilistic Reasoning over Time
Artificial Neural Network dan Deep Learning
K-NN dan SVM
Learning Probabilistic Models

46. References
Widodo Budiharto and Derwin Suhartono (2015), Artificial Intelligence, Andi offset Publisher.
Stuart Russell, Peter Norvig Artificial Intelligence : A Modern Approach. Pearson Education. New Jersey. ISBN: